Academic literature on the topic 'Tesseract-ocr for License Plate Recognition'

License Plate Recognition (LPR) systems are frequently utilized in various access controls and security applications. In this thesis, an experimental constraint based real-time License Plate Recognition system is designed, and implemented in Java platform. Many of the available constraint based methods worked under strict restrictions such as plate color, fixed illumination and designated routes, whereas, only the license plate geometry and format constraints are used in this developed system. These constraints are built on top of the current Turkish license plate regulations. The plate localization algorithm is based on vertical edge features where constraints are used to filter out non-text regions. Vertical and horizontal projections are used for character segmentation and Multi Layered Perceptron (MLP) based Optical Character Recognition (OCR) module has been implemented for character identification. The extracted license plate characters are validated against possible license plate formats during the recognition process. The system is tested both with Turkish and foreign license plate images including various plate orientation, image quality and size. An accuracy of 92% is achieved for license plate localization and %88 for character segmentation and recognition.

Automatinis transporto priemonių registracijos numerio atpažinimas atlieka svarbų vaidmenį daugelyje programinių paketų, taikomų tiek valstybinėse institucijose, tiek ir privačiose kompanijose, kuriuose yra naudojamos įvairios atpažinimo algoritmų technologijos. Tačiau net ir dabar neįmanoma sukurti idealiai veikiančios sistemos, kuri palieka laisvę efektyviausių algoritmų paieškai. Šio tiriamojo darbo tikslas yra išanalizuoti alternatyvius automobilio numerio lokalizacijos ir kitų atpažinimo etapų algoritmus, jų efektyvumą bei adaptyvumą. Analizė atliekama juos realizuojant ir atliekant tyrimus su testiniais duomenimis bei iš jų gautais rezultatais. Iš realizuotos alternatyvių atpažinimo algoritmų sistemos gauti rezultatai parodė, kad kiekviena atpažinimo proceso grandis yra jautri įvairiems faktoriams, kurių kitimas lemia tarpinių bei galutinių rezultatų variaciją.<br>Automatic license plate recognition plays an important role in numerous applications and a number of techniques have been proposed for public institutions or private companies. However, even now it is impossible to design a perfect and operational recognition system. It still leaves a space for creativity and research of the most effective algorithms. The main objective of this dissertation is to analyze alternatives of licese plate localization and other stages of recognition, their efficiency and adaptability. Selected means of this research are such as implementation of algorithms, analysis of testing data and test results. Every stage of recognition process is extremely sensitive to different factors which determinate variation of transitional and final results. This was proven by analysis of alternative algorithms functionality.

Automatinis transporto priemonių registracijos numerio atpažinimas atlieka svarbų vaidmenį daugelyje programinių paketų, taikomų tiek valstybinėse institucijose, tiek ir privačiose kompanijose, kuriuose yra naudojamos įvairios atpažinimo algoritmų technologijos. Tačiau net ir dabar neįmanoma sukurti idealiai veikiančios sistemos, kuri palieka laisvę efektyviausių algoritmų paieškai. Šio tiriamojo darbo tikslas yra išanalizuoti alternatyvius automobilio numerio lokalizacijos ir kitų atpažinimo etapų algoritmus, jų efektyvumą bei adaptyvumą. Analizė atliekama juos realizuojant ir atliekant tyrimus su testiniais duomenimis bei iš jų gautais rezultatais. Iš realizuotos alternatyvių atpažinimo algoritmų sistemos gauti rezultatai parodė, kad kiekviena atpažinimo proceso grandis yra jautri įvairiems faktoriams, kurių kitimas lemia tarpinių bei galutinių rezultatų variaciją.<br>Automatic license plate recognition plays an important role in numerous applications and a number of techniques have been proposed for public institutions or private companies. However, even now it is impossible to design a perfect and operational recognition system. It still leaves a space for creativity and research of the most effective algorithms. The main objective of this dissertation is to analyze alternatives of licese plate localization and other stages of recognition, their efficiency and adaptability. Selected means of this research are such as implementation of algorithms, analysis of testing data and test results. Every stage of recognition process is extremely sensitive to different factors witch determinate variation of transitional and final results. This was proven by analysis of alternative algorithms functionality.

The theme of this thesi’s deals with the detection and recognition of car license plate from pictures made of screening machine situated on a crassing or inside a car. The thesis si divided into two basic parts. First deals with searching for presence of licence plate in the picture. If the marque was found, we continue the second part of the program which identificates the found license plate. The first part of program aspires to find the licence plate by the edge detectors. The second part classifies characters by the method based on an analytical description.

This thesis describes the design and workflow of creating an image processing application in Android system, and what are the possibilities in choosing development environment and how to implement them. Then I am writing about my solutions of creating applications, graphical user interface and an interface for Android. I am describing my approach in the design and functionality of the application, communication with the camera, storing and retrieving data. Further I explain which algorithms were implemented for image processing and image evaluation. Product of this thesis is a functioning application that allows to its user to capture images and video stream. The algorithm evaluates the entering data and shows the location of the number plate. The application also allows recognizing texts and numbers from images. There are other various practical features and options implemented within the application.

La lecture automatique de plaques d’immatriculation de véhicule est considérée comme une approche de surveillance de masse. Elle permet, grâce à la détection /localisation ainsi que la reconnaissance optique, d’identifier un véhicule dans les images ou les séquences d’images. De nombreuses applications comme le suivi du trafic, la détection de véhicules volés, le télépéage ou la gestion d’entrée / sortie des parkings utilise ce procédé. Or malgré d’important progrès enregistré depuis l’apparition des premiers prototypes en 1979 accompagné d’un taux de reconnaissance parfois impressionnant, notamment grâce aux avancés en recherche scientifique et en technologie des capteurs, les contraintes imposés pour le bon fonctionnement de tels systèmes en limitent les portées. En effet, l’utilisation optimale des techniques de localisation et de reconnaissance de plaque d’immatriculation dans les scénarii opérationnels nécessite des conditions d’éclairage contrôlées ainsi qu’une limitation dans de la pose, de vitesse ou tout simplement de type de plaque. La lecture automatique de plaques d’immatriculation reste alors un problème de recherche ouvert. La contribution majeure de cette thèse est triple. D’abord une nouvelle approche robuste de localisation de plaque d’immatriculation dans des images ou des séquences d’images est proposée. Puis, l’amélioration de la qualité des plaques localisées est traitée par une adaptation de technique de super-résolution. Finalement, un modèle unifié de localisation et de super-résolution est proposé permettant de diminuer la complexité temporelle des deux approches combinées<br>Automatic reading of vehicle license plates is considered an approach to mass surveillance. It allows, through the detection / localization and optical recognition to identify a vehicle in the images or video sequences. Many applications such as traffic monitoring, detection of stolen vehicles, the toll or the management of entrance/ exit parking uses this method. Yet in spite of important progress made since the appearance of the first prototype sin 1979, with a recognition rate sometimes impressive thanks to advanced science and sensor technology, the constraints imposed for the operation of such systems limit laid. Indeed, the optimal use of techniques for localizing and recognizing license plates in operational scenarios requiring controlled lighting conditions and a limitation of the pose, velocity, or simply type plate. Automatic reading of vehicle license plates then remains an open research problem. The major contribution of this thesis is threefold. First, a new approach to robust license plate localization in images or image sequences is proposed. Then, improving the quality of the plates is treated with a localized adaptation of super-resolution technique. Finally, a unified model of location and super-resolution is proposed to reduce the time complexity of both approaches combined

碩士<br>國立臺灣海洋大學<br>電機工程學系<br>103<br>Science and technology is more and more flourishing , that the vehicle is to be need in each family. The vehicle is already one part of life, and amount of world vehicle also at keep on on the increase, the public order transportation caused by a great deal of car is as the most important as management problem. The car has already become main vehicle at present, and then the license plate is like the identity card of car, want the words to carry on the effective management to car are from the license plate begin most physically. It is already a necessary tool to recognize for the sake of solution above problem license plate. This thesis proposes the image processing and Tesseract-OCR technology in the implementation of a number plate recognition system . The related image processing need for license plate recognition technology is being realized by the open source computer vision library (OpenCV). Image processing using color conversion to convert the color image to a grayscale image and using fuzzy processed technique for reduce to the noise. License plate positioning are processed using edge detection and morphology method , which look for some images like the license plate and to sieve it out and we using some characteristics to choose the correct license plate.After using image processing to license plate image and to eliminate that not belong to the license plate character image.Then the license plate character image had be find out to use Tesseract-OCR to identify that the find character image to compare together and to obtain similarity a number plate character. In this thesis the Tesseract-OCR is an open source of optical character recognition engine, it can support many character and language to identify and with open source computer vision library(OpenCV),on the Internet is easy tool to be obtained . The proposed system can be quickly implemented in the multiple platforms and shorten development time . The system can be useful in many areas,because it can change according to different countries to identify characters .